Membership Inference Attack on CIFAR-100 balanced (evaluation set)
99.17AUROCInt. Outs*
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| Int. Outs*Target Model=DenseNet, Requires training=true, Evaluation data used=60%2022.03 | 99.17 | 97.68 | |
| Int. Outs*Target Model=ResNet, Requires training=true, Evaluation data used=60%2022.03 | 96.59 | 91.57 | |
| Int. Outs*Target Model=ResNext, Requires training=true, Evaluation data used=60%2022.03 | 93.62 | 86.38 | |
| Adversarial DistanceTarget Model=ResNext, Requires training=false, Evaluation data used=100%2022.03 | 89.24 | 89.1 | |
| WB*Target Model=ResNet, Requires training=true, Evaluation data used=60%2022.03 | 87.51 | 79.73 | |
| Adversarial DistanceTarget Model=ResNet, Requires training=false, Evaluation data used=100%2022.03 | 84.53 | 85.45 | |
| WB*Target Model=ResNext, Requires training=true, Evaluation data used=60%2022.03 | 84.52 | 76.46 | |
| Adversarial DistanceTarget Model=AlexNet, Requires training=false, Evaluation data used=100%2022.03 | 84.35 | 85.12 | |
| Adversarial DistanceTarget Model=DenseNet, Requires training=false, Evaluation data used=100%2022.03 | 82.78 | 82.63 | |
| WB*Target Model=AlexNet, Requires training=true, Evaluation data used=60%2022.03 | 80.33 | 74.03 | |
| WB*Target Model=DenseNet, Requires training=true, Evaluation data used=60%2022.03 | 79.38 | 71.92 | |
| Grad w*Target Model=AlexNet, Requires training=true, Evaluation data used=60%2022.03 | 78.76 | 74.32 | |
| Grad w*Target Model=ResNext, Requires training=true, Evaluation data used=60%2022.03 | 77.8 | 73.47 | |
| Grad x*Target Model=ResNext, Requires training=true, Evaluation data used=60%2022.03 | 77.54 | 73.47 | |
| Grad x*Target Model=AlexNet, Requires training=true, Evaluation data used=60%2022.03 | 77.2 | 73.43 | |
| Mentr.Target Model=AlexNet, Requires training=false, Evaluation data used=100%2022.03 | 77.11 | 74.16 | |
| Mentr.Target Model=ResNext, Requires training=false, Evaluation data used=100%2022.03 | 76.87 | 75.28 | |
| LossTarget Model=AlexNet, Requires training=false, Evaluation data used=100%2022.03 | 76.69 | 74.14 | |
| Grad NormTarget Model=AlexNet, Requires training=false, Evaluation data used=100%2022.03 | 76.58 | 74.19 | |
| Grad x*Target Model=DenseNet, Requires training=true, Evaluation data used=60%2022.03 | 75.81 | 71.81 | |
| Mentr.Target Model=DenseNet, Requires training=false, Evaluation data used=100%2022.03 | 74.21 | 72.69 | |
| Grad w*Target Model=DenseNet, Requires training=true, Evaluation data used=60%2022.03 | 73.12 | 72.59 | |
| Grad NormTarget Model=ResNext, Requires training=false, Evaluation data used=100%2022.03 | 73.06 | 75.74 | |
| LossTarget Model=ResNext, Requires training=false, Evaluation data used=100%2022.03 | 72.57 | 75.17 | |
| SoftmaxTarget Model=ResNext, Requires training=false, Evaluation data used=100%2022.03 | 72.37 | 74.84 | |
| Grad NormTarget Model=DenseNet, Requires training=false, Evaluation data used=100%2022.03 | 71.3 | 73.81 | |
| LossTarget Model=DenseNet, Requires training=false, Evaluation data used=100%2022.03 | 70.85 | 72.61 | |
| SoftmaxTarget Model=DenseNet, Requires training=false, Evaluation data used=100%2022.03 | 70.52 | 72.11 | |
| Grad x*Target Model=ResNet, Requires training=true, Evaluation data used=60%2022.03 | 68.48 | 63.58 | |
| SoftmaxTarget Model=AlexNet, Requires training=false, Evaluation data used=100%2022.03 | 68 | 65.34 | |
| Grad w*Target Model=ResNet, Requires training=true, Evaluation data used=60%2022.03 | 61.98 | 62.72 | |
| Grad NormTarget Model=ResNet, Requires training=false, Evaluation data used=100%2022.03 | 59.93 | 62.56 | |
| Mentr.Target Model=ResNet, Requires training=false, Evaluation data used=100%2022.03 | 59.1 | 61.39 | |
| LossTarget Model=ResNet, Requires training=false, Evaluation data used=100%2022.03 | 58.66 | 61.29 | |
| Int. Outs*Target Model=AlexNet, Requires training=true, Evaluation data used=60%2022.03 | 57.92 | 56.36 | |
| SoftmaxTarget Model=ResNet, Requires training=false, Evaluation data used=100%2022.03 | 55.45 | 57.4 |